Table 4.
The comparison of related studies for the automatic analysis of COVID-19 pneumonia from chest x-ray imaging utilizing artificial intelligence.
| Study | Number of Cases | Data Source COVID-19 | Accuracy (%) |
|---|---|---|---|
| Wang and Wong (2020) | 53 COVID-19 (+)5526 COVID-19 (-)8066 Healthy | Wang | 93.30 |
| Polat et al. (2021) | 299 COVID-191522 Pneumonia | Cohen | 97.10 |
| Sethy, Behera, Ratha, and Biswas (2020) | 25 COVID-19 (+)25 COVID-19 (-) | Cohen | 95.38 |
| Luz, Silva, Silva, and Moreira (2020) | 183 COVID-19 (+)8066 Healthy | Wang | 94.30 |
| Khobahi et al. (2020) | 76 COVID-19 (+)5526 Pneumonia8066 Healthy | Cohen | 93.50 |
| Zhang, Xie, Li, Shen, and Xia (2020) | 493 COVID-19 (+)24,596 Pneumonia18,774 Healthy | Cohen, Kaggle | 83.61 |
| Rahimzadeh and Attar (2020) | 118 COVID-19 (+)6037 Pneumonia8868 Healthy | Cohen | 91.40 |
| Hall, Paul, Goldgof, and Goldgof (2020) | 135 COVID-19 (+)208 Pneumonia | Cohen, SIRM, Radiopeadia | 93.12 |
| Majeed, Rashid, Ali, and Asaad, (2020) | 184 COVID-19 (+)6290 Healthy | Cohen, Kaggle | 97.00 |
| El Asnaoui and Chawki (2020) | 231 COVID-19 (+)4273 Pneumonia1583 Healthy | Cohen | 92.18 |
| This study | 368 COVID-19 (+)850 Other Pneumonia | Combined dataset(Kaggle, Cohen, Wang) | 94.96 |